A densely interconnected convolutional neural network-based approach to identify COVID-19 from Chest X-ray Images

A densely interconnected convolutional neural network-based approach to identify COVID-19 from Chest X-ray Images

The novel Corona Virus (COVID-19) has spread so rapidly that cause a devastating effect on public well-being and create an emergency around the world. Hence, the rapid identification of COVID-19 has become a challenging work within a short period. Clinical trials of patients with COVID-19 have shown...

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Bibliographic Details
Main Authors: Alfaz, Nazia, Sarwar, Talha, Das, Argho, Noorhuzaimi, Mohd Noor
Format: Conference or Workshop Item
Language:English
English
Published: Springer Science and Business Media Deutschland GmbH 2022
Subjects:
Q Science (General)
QA75 Electronic computers. Computer science
QA76 Computer software
T Technology (General)
TA Engineering (General). Civil engineering (General)
Online Access:http://umpir.ump.edu.my/id/eprint/39633/1/A%20Densely%20Interconnected%20Convolutional%20Neural%20Network-Based%20Approach.pdf
http://umpir.ump.edu.my/id/eprint/39633/2/A%20densely%20interconnected%20convolutional%20neural%20network-based%20approach%20to%20identify%20COVID-19%20from%20Chest%20X-ray%20Images_ABS.pdf

Internet

http://umpir.ump.edu.my/id/eprint/39633/1/A%20Densely%20Interconnected%20Convolutional%20Neural%20Network-Based%20Approach.pdf
http://umpir.ump.edu.my/id/eprint/39633/2/A%20densely%20interconnected%20convolutional%20neural%20network-based%20approach%20to%20identify%20COVID-19%20from%20Chest%20X-ray%20Images_ABS.pdf

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